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AvanzadocourseAcceso por bootcamp
CI/CD for AI Systems Guide
64
Lecciones
8
Módulos
🎓
Acceso por bootcamp
Lo que aprenderás
✓Set up GitHub Actions workflows for AI projects from scratch
✓Automate pytest execution with matrix testing and dependency caching
✓Implement AI-specific CI checks: prompt regression testing and cost estimation
✓Manage secrets and environment variables securely in pipelines
✓Build and push Docker images automatically with layer caching
✓Create deployment pipelines with staging, approval gates, and production
✓Implement rollback strategies for failed deployments
✓Build production-grade pipelines with notifications and monitoring
¿Para quién es?
- •AI Engineers who deploy manually and want to automate their delivery pipeline
- •Teams that need consistent, automated testing and deployment for AI applications
- •Developers who have Docker containers ready and need CI/CD to automate the flow
- •Tech leads establishing DevOps practices for AI teams
- •Anyone in the AI Engineering Path ready to automate their production workflow
Requisitos
- •Git & GitHub proficiency (Guide #4)
- •Docker fundamentals: Dockerfiles, Docker Compose (Guide #15)
- •Testing basics: pytest, unit tests (Guide #13)
- •Python intermediate
- •No prior CI/CD experience required
Contenido del curso
1Módulo 1: Introducción a CI/CD y GitHub Actions — Guía para el Creador8 lecciones
2Módulo 2: Testing Automatizado en CI — Guía para el Creador8 lecciones
3Módulo 3: AI-Specific CI Checks — Guía para el Creador8 lecciones
4Módulo 4: Secrets y Environment Management — Guía para el Creador8 lecciones
5Módulo 5: Docker en CI/CD — Guía para el Creador8 lecciones
6Módulo 6: Deployment Pipelines — Guía para el Creador8 lecciones
7Módulo 7: Monitoring, Notifications y Advanced Patterns — Guía para el Creador8 lecciones
8Módulo 8: Proyecto Integrador — Production AI Pipeline — Guía para el Creador8 lecciones
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